These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

178 related articles for article (PubMed ID: 31925684)

  • 1. Dissolved oxygen prediction using a new ensemble method.
    Kisi O; Alizamir M; Docheshmeh Gorgij A
    Environ Sci Pollut Res Int; 2020 Mar; 27(9):9589-9603. PubMed ID: 31925684
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Extreme learning machines: a new approach for modeling dissolved oxygen (DO) concentration with and without water quality variables as predictors.
    Heddam S; Kisi O
    Environ Sci Pollut Res Int; 2017 Jul; 24(20):16702-16724. PubMed ID: 28560629
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Performance of ANFIS versus MLP-NN dissolved oxygen prediction models in water quality monitoring.
    Najah A; El-Shafie A; Karim OA; El-Shafie AH
    Environ Sci Pollut Res Int; 2014 Feb; 21(3):1658-1670. PubMed ID: 23949111
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Implementation of data intelligence models coupled with ensemble machine learning for prediction of water quality index.
    Abba SI; Pham QB; Saini G; Linh NTT; Ahmed AN; Mohajane M; Khaledian M; Abdulkadir RA; Bach QV
    Environ Sci Pollut Res Int; 2020 Nov; 27(33):41524-41539. PubMed ID: 32686045
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Artificial neural network modeling of dissolved oxygen in reservoir.
    Chen WB; Liu WC
    Environ Monit Assess; 2014 Feb; 186(2):1203-17. PubMed ID: 24078053
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Prediction of biochemical oxygen demand at the upstream catchment of a reservoir using adaptive neuro fuzzy inference system.
    Chiu YC; Chiang CW; Lee TY
    Water Sci Technol; 2017 Oct; 76(7-8):1739-1753. PubMed ID: 28991790
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Modeling hourly dissolved oxygen concentration (DO) using two different adaptive neuro-fuzzy inference systems (ANFIS): a comparative study.
    Heddam S
    Environ Monit Assess; 2014 Jan; 186(1):597-619. PubMed ID: 24057665
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Comparative study of artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS) and multiple linear regression (MLR) for modeling of Cu (II) adsorption from aqueous solution using biochar derived from rambutan (Nephelium lappaceum) peel.
    Wong YJ; Arumugasamy SK; Chung CH; Selvarajoo A; Sethu V
    Environ Monit Assess; 2020 Jun; 192(7):439. PubMed ID: 32556670
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Performance evaluation of artificial intelligence paradigms-artificial neural networks, fuzzy logic, and adaptive neuro-fuzzy inference system for flood prediction.
    Tabbussum R; Dar AQ
    Environ Sci Pollut Res Int; 2021 May; 28(20):25265-25282. PubMed ID: 33453033
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Assessing the biochemical oxygen demand using neural networks and ensemble tree approaches in South Korea.
    Kim S; Alizamir M; Zounemat-Kermani M; Kisi O; Singh VP
    J Environ Manage; 2020 Sep; 270():110834. PubMed ID: 32507742
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Dissolved oxygen modelling of the Yamuna River using different ANFIS models.
    Arora S; Keshari AK
    Water Sci Technol; 2021 Nov; 84(10-11):3359-3371. PubMed ID: 34850733
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A novel multi-model data-driven ensemble approach for the prediction of particulate matter concentration.
    Umar IK; Nourani V; Gökçekuş H
    Environ Sci Pollut Res Int; 2021 Sep; 28(36):49663-49677. PubMed ID: 33939094
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Modelling biochemical oxygen demand using improved neuro-fuzzy approach by marine predators algorithm.
    Adnan RM; Dai HL; Kisi O; Heddam S; Kim S; Kulls C; Zounemat-Kermani M
    Environ Sci Pollut Res Int; 2023 Sep; 30(41):94312-94333. PubMed ID: 37531049
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A hybrid air quality early-warning framework: An hourly forecasting model with online sequential extreme learning machines and empirical mode decomposition algorithms.
    Sharma E; Deo RC; Prasad R; Parisi AV
    Sci Total Environ; 2020 Mar; 709():135934. PubMed ID: 31869708
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Improving one-dimensional pollution dispersion modeling in rivers using ANFIS and ANN-based GA optimized models.
    Seifi A; Riahi-Madvar H
    Environ Sci Pollut Res Int; 2019 Jan; 26(1):867-885. PubMed ID: 30415370
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Application of soft computing to predict water quality in wetland.
    Pham QB; Mohammadpour R; Linh NTT; Mohajane M; Pourjasem A; Sammen SS; Anh DT; Nam VT
    Environ Sci Pollut Res Int; 2021 Jan; 28(1):185-200. PubMed ID: 32808123
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Research on air pollutant concentration prediction method based on self-adaptive neuro-fuzzy weighted extreme learning machine.
    Li Y; Jiang P; She Q; Lin G
    Environ Pollut; 2018 Oct; 241():1115-1127. PubMed ID: 30029320
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Modeling daily water temperature for rivers: comparison between adaptive neuro-fuzzy inference systems and artificial neural networks models.
    Zhu S; Heddam S; Nyarko EK; Hadzima-Nyarko M; Piccolroaz S; Wu S
    Environ Sci Pollut Res Int; 2019 Jan; 26(1):402-420. PubMed ID: 30406582
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Estimation of daily dissolved oxygen concentration for river water quality using conventional regression analysis, multivariate adaptive regression splines, and TreeNet techniques.
    Nacar S; Mete B; Bayram A
    Environ Monit Assess; 2020 Nov; 192(12):752. PubMed ID: 33159587
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Comparison of the performance of decision tree (DT) algorithms and extreme learning machine (ELM) model in the prediction of water quality of the Upper Green River watershed.
    Anmala J; Turuganti V
    Water Environ Res; 2021 Nov; 93(11):2360-2373. PubMed ID: 34528328
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.